A position estimating technique has been proposed in which a mobile terminal such as a mobile phone, which is an example of a terminal apparatus, makes wireless communications with a plurality of base stations, and estimates a location of the mobile terminal by utilizing attenuation of received signal strengths depending on a distance to the mobile terminal from each of the plurality of base stations. For example, the base station may be an AP (Access Point) used in WiFi (Wireless Fidelity, registered trademark).
According to such a position estimating technique, the mobile terminal collects, in advance, IDs (Identifiers) of the plurality of base stations and RSSIs (Received Signal Strength Indicators) received at each location. From the IDs of the plurality of base stations and values of the RSSIs received at each location, an RSSI feature vector that is uniquely determined for each location is created, and a location model is created for each location using the RSSI feature vector. The location model may make a reference to a database indicating the location where the signals are received from the base stations, the base stations from which the signals are received by the mobile terminal at the location, and the RSSIs of the signals received by the mobile terminal at the location. When estimating the location, the RSSIs of the signals received by the mobile terminal from the base stations are collated with the location model, in order to estimate the location of the mobile terminal. Generally, the location model may be created by methods such as the k-NN (k-Nearest Neighbor algorithm) method, probability method based on probability distribution, non-parametric method, pattern matching method, or the like.
When the number of locations is large, the RSSI of the signal received from the base station by the mobile terminal needs to be collated with a large number of location models. A large storage capacity must be secured in order to store the large number of location models in the mobile terminal, because an amount of information of each location model is relatively later. However, the storage capacity of the mobile terminal is limited, and in some cases, a sufficiently large storage capacity cannot be secured to store the large number of location models. Hence, it is conceivable to simply decimate the large number of location models with which the RSSI of the signal received from the base station by the mobile terminal needs to be collated. But since it is impossible to know the location of the mobile terminal in advance, the position estimating accuracy deteriorates unless all of the location models are stored in the mobile terminal. On the other hand, although the position estimating accuracy can be maintained by securing the sufficiently large storage capacity to store all of the location models in the mobile terminal, a memory having the large storage capacity needs to be provided in the mobile terminal, and a cost of the mobile terminal increases due to the need to provide such a memory having the large storage capacity.
Conventionally, it is difficult to reduce the storage capacity for storing the location models, without sacrificing the position estimating accuracy.
Examples of the related art include Japanese Laid-Open Patent Publications No. 2012-145586 and No. 2013-053930.